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        "author": "Camille Maumet",
        "author_email": "c.m.j.maumet@warwick.ac.uk",
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            "Development Status :: 3 - Alpha",
            "License :: OSI Approved :: MIT License",
            "Programming Language :: Python :: 3",
            "Topic :: Utilities"
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        "description": "\n# NIDM-Results for FSL\n\n[![Build Status](https://travis-ci.org/incf-nidash/nidmresults-fsl.svg?branch=master)](https://travis-ci.org/incf-nidash/nidmresults-fsl)\n\nExport mass-univariate neuroimaging results computed in FSL (using FEAT) as NIDM-Results packs.\n\nA *NIDM-Results pack* is a compressed file containing a NIDM-Results serialization and some or all of the referenced image data files in compliance with [NIDM-Results specification](http://nidm.nidash.org/specs/nidm-results.html).\n\n##### Usage\n```\nusage: nidmfsl [-h] [-g GROUP_NAME NUM_SUBJECTS] [-o OUTPUT_NAME] [-d]\n               [-n NIDM_VERSION] [--version]\n               feat_dir\n\nNIDM-Results exporter for FSL Feat.\n\npositional arguments:\n  feat_dir              Path to feat directory.\n\noptional arguments:\n  -h, --help            show this help message and exit\n  -g GROUP_NAME NUM_SUBJECTS, --group GROUP_NAME NUM_SUBJECTS\n                        Group label followed by number of subjects\n  -o OUTPUT_NAME, --output_name OUTPUT_NAME\n                        Name of the output. A \".nidm.zip\" or \".nidm\" (when -d\n                        is used) suffix will be appended.\n  -d, --directory-output\n                        Produces a .nidm directory rather than a .nidm.zip\n                        file.\n  -n NIDM_VERSION, --nidm_version NIDM_VERSION\n                        NIDM-Results version to use (default: latest).\n  --version             show program's version number and exit\n```\n\n\n##### Installation\n\nTo install, run the below command in the bash terminal.\n```\n    pip install nidmfsl\n```\n\n##### Compatible with \nFSL version 5.0.9\n\n##### Testing\n\n###### Requirements\n\nTo run the tests for this repository, the following must be installed\n\n- Git LFS. Installation instructions for Git LFS can be found [here](https://git-lfs.github.com/).\n\n- The python packages `vcr` and `ddt`. These can be installed using the below commands in the bash terminal:\n\n```\npip install vcrpy\npip install ddt\n```\n\nIn addition, the test data must also be downloaded from the `nidmresults-examples` repository to `<path_to_this_repository>/test/data/nidmresults-examples`.\n\n```\ngit lfs clone https://github.com/incf-nidash/nidmresults-examples.git <path_to_this_repository>/test/data/nidmresults-examples\n```\n\n###### Running the tests\n\nThe below command can be used to generate the test cases.\n```\npython <path_to_this_repository>/test/export_test_battery.py\n```\n\nFolowing this, the test cases can be verified against the ground truth provided in the `nidmresults-examples` repository using the below command.\n```\ncd <path_to_this_repository>/test/\npython -m unittest discover\n```\n\n\n",
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